AI - ML DevOps Engineer
- Location
- United States
- Listed
- Today
About the role
- Primary City/State: Virtual Arizona
- Category: Data Intelligence
- Shift: Day
- Department: Augmented Intelligence
- Hours: Monday-Friday Days
Location: Remote -- Must be located in Arizona -- Occasional on site as needed.
Great care starts with great people. (Like you.)
At HonorHealth, you'll find something special. From humble beginnings in 1927 to one of Arizona's largest nonprofit healthcare systems, our culture is built on warmth and neighborly kindness. Behind every smile is a highly skilled professional with deep expertise and an unwavering dedication to what matters most - caring for the health and well-being of people and communities across the greater Phoenix area.
Job Summary
The AI / ML DevOps Engineer designs, develops, deploys, and supports scalable machine learning solutions that enable advanced analytics and AI capabilities across HonorHealth. This role operationalizes models and pipelines, monitors performance, and partners with data, engineering, and stakeholders to deliver reliable solutions aligned to governance and data handling expectations.
The role partners closely with data engineers, data scientists, AI model developers, platform teams, and business stakeholders to translate complex needs into production-ready deployments, monitor ongoing performance, and continuously improve AI/ML capabilities aligned to governance and operational standards.
Essential Functions
- Design and implementation of the environment that deploys scalable AI/ML solutions, including predictive models, large language model use cases, and agentic workflows that support clinical, operational, and business objectives.
- Develops and maintains end-to-end machine learning and RAG pipelines supporting data ingestion, application feature engineering, training, evaluation, deployment, and lifecycle management.
- Architects and supports production-grade DevOps practices, including CI/CD, model versioning, automated testing, monitoring, alerting, retraining, and rollback strategies.
- Deploys and manages AI/ML applications in cloud environments, ensuring solutions are secure, reliable, performant, and operationally supportable.
- Implements observability and performance evaluation practices to manage compute resource utilization, performance, and cost efficiency. Works with AI development team to a continuous improvement feedback loop.
- Ensures AI/ML and agentic solutions comply with data governance, privacy, security, and responsible AI expectations, including HIPAA-aligned practices where applicable.
- Creates and maintains technical documentation for deployments, workflows, operational procedures, assumptions, limitations, and support processes.
- Troubleshoots complex pipeline, infrastructure, model, and integration issues; implements fixes and drives continuous improvement in operational stability and delivery efficiency.
- Core Skills:
Additional information
- Hands-on experience with cloud-native AI/ML services and infrastructure, preferably in Google Cloud Platform (GCP), including services for training, inference, orchestration, and scalable compute
- Proficiency info MLOps, DevOps, and software engineering practices such as CI/CD, Git-based workflows, containerization, Infrastructure as Code, and automated testing
- Proficiency with establishing connections via API calls and MCP servers.
- Strong SQL and data engineering skills with experience in large-scale data processing, backend engineering, and integration across enterprise data platforms
- Experience with API development and systems integration to embed AI/ML capabilities into enterprise applications and workflows
- Strong analytical and problem-solving skills with the ability to diagnose issues across data, models, infrastructure, and orchestration layers
- Excellent communication and collaboration skills with the ability to document and explain technical concepts clearly to both technical and non-technical stakeholders
- Performs other duties as assigned.
Education
- Bachelors Computer Science, Data Science, Engineering, Artificial Intelligence, Machine Learning, Mathematics, Statistics, or a related quantitative field; or 4 years' relevant experience. Required
Experience
- 3 years, of progressive experience in DevOps within a Cloud deployment in AI/ML Ops, data engineering, or related software engineering roles, including at least 1 year deploying and operating AI/ML production workloads. Required
License and Certifications
We're all in for your career.
From HonorHealth's careers page, first listed on Rolev.ai on November 9, 2026. Rolev.ai is not the employer.
How Rolev.ai helps with this application
Rolev.ai is a job search and application tool for US job seekers. For this AI - ML DevOps Engineer role at HonorHealth, it shows how your resume fits, tailors your resume to the posting, and prepares the application for you to review.
See how you fit
Openings from employer career sites are ranked against your whole resume—and searchable inside Claude, ChatGPT, and Cursor via Rolev.ai MCP.
Tailor without inventing
Every change to your resume is checked against your original. New experience goes in only with your yes—zero fabricated claims.
Draft the full kit
Tailored and Full Match resumes, role-specific cover letters, and answers to employer screening questions are prepared in seconds.
1-Click Extension Autofill
The Chrome extension fills the employer's Greenhouse, Workday, Lever, or Ashby form in 1 click. You review it and press Submit.
Common questions
Where is the AI - ML DevOps Engineer job at HonorHealth located?
This AI - ML DevOps Engineer position at HonorHealth is located in United States. Always check HonorHealth's application page for specific state eligibility or relocation policies.
How do I apply for the AI - ML DevOps Engineer position at HonorHealth?
This listing links directly to HonorHealth's Workday application page. You can apply directly on HonorHealth's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Workday application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.